Model-based aversive learning in humans is supported by preferential task state reactivation
[ recordings from 7 participants performing an auditory imagery task, wherein subjects imagined sounds produced by objects from semantic categories (animals and tools) for 5-second intervals. EEG signals were acquired using a 64-channel BioSemi ActiveTwo system sampled at 2048 Hz, with concurrent electrooculography and physiological monitoring. The dataset supports research in semantic decoding and brain-computer interface applications using imagined auditory stimuli.
…Movement explained significant variance in the neural data over and above that…
This dataset comprises simultaneous 64-channel EEG and 3T fMRI recordings from 16 subjects performing motor imagery and neurofeedback tasks. Participants were randomly assigned to receive either mono-dimensional or bi-dimensional neurofeedback displays during five experimental runs with alternating rest and task blocks. The dataset includes raw EEG data in Brain Vision format, preprocessed EEG data, BOLD fMRI acquisitions, computed neurofeedback scores from both modalities (EEG and fMRI), and event timing files, providing a comprehensive resource for multimodal neuroimaging data integration studies.